Sven Jäger

mRNA-GPT is a generative model that optimizes full-length mRNA sequences by jointly optimizing all three regions, achieving Pareto-optimal designs and outperforming existing methods.

The paper applies a novel active learning strategy, DEW-DROP, to improve protein structure prediction efficiency and data selection for two protein datasets.

CodonBERT is a large language model for mRNA design and optimization that outperforms previous methods on a flu vaccine dataset.

The paper develops two novel active learning batch selection methods for drug discovery, showing significant improvements over existing methods across multiple datasets.

This study optimizes LCR experimental parameters to improve plasmid assembly efficiency by analyzing the effects of BO melting temperatures and secondary structure inhibitors.